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Supplement of Atmos. Chem. Phys., 16, 10215–10228, 2016http://www.atmos-chem-phys.net/16/10215/2016/doi:10.5194/acp-16-10215-2016-supplement© Author(s) 2016. CC Attribution 3.0 License.
Supplement of
Characteristics of total gaseous mercury (TGM) concentrations in an in-dustrial complex in South Korea: impacts from local sourcesYong-Seok Seo et al.
Correspondence to: Seung-Muk Yi ([email protected])
The copyright of individual parts of the supplement might differ from the CC-BY 3.0 licence.
2
49
Fig. S1. Frequency of counts of measured wind direction occurrence by season in this 50 study. 51 52
3
53
Fig. S2. Sectoral contribution of emissions of (a) South Korea, (b) Gyeongsangbuk-do 54 and (c) Pohang for CO, NOx, SOx, TSP VOC and NH3. 55
56
4
Sectoral contribution of emissions 57
In South Korea, the NOx emissions were highest, followed by VOC, CO, SOx, NH3, TSP, 58
PM10 and PM2.5 (Fig. S2(a)). In Gyeongsangbuk-do, the NOx emissions were highest, 59
followed by CO, VOC, SOx, NH3, and TSP, PM10 and PM2.5 which is similar trend to South 60
Korea (Fig. S2(b)). However, Pohang showed a different pattern with the highest NOx 61
emissions, followed by SOx, VOC, CO, TSP, PM10, PM2.5 and NH3 (Fig. S2(c)). 62
Point source (combustion in energy industries + combustion in manufacturing industries + 63
production processes + waste treatment and disposal) in South Korea accounted for 64
1,226,609 tons (34.6% of total emissions in South Korea) of the air pollutants. 65
Gyeongsangbuk-do has a similar trend with 106,439 tons (35.8% of total emissions in 66
Gyeongsangbuk-do) of the air pollutants. However, Pohang has a significantly high 67
contribution with 56,144 tons (69.2% of total emissions in Pohang) of the air pollutants. 68
Area source (non-industrial combustion + storage and distribution of fuels + solvent 69
utilization + agriculture + other area sources) in South Korea accounted for 1,055,461 tons 70
(29.8% of total emissions in South Korea) of the air pollutants. Gyeongsangbuk-do has a 71
similar trend with 90,982 tons (30.6% of total emissions in Gyeongsangbuk-do) of the air 72
pollutants. However, Pohang has a less contribution with 6,903 tons (8.5% of total emissions 73
in Pohang) of the air pollutants. 74
Mobile source (road transport + non-road transport) in South Korea accounted for 75
1,261,782 tons (35.6% of total emissions in South Korea) of the air pollutants. 76
Gyeongsangbuk-do has a similar contribution with 99,709 tons (33.6% of total emissions in 77
Gyeongsangbuk-do) of the air pollutants. Pohang also has a lower contribution with 18,048 78
tons (22.3% of total emissions in Pohang) of the air pollutants. 79
80
5
Table S1. Source Classification Categories (SCC) in CAPSS. The fugitive dust and 81 biomass were excluded. 82
Emission characteristics SCC1 (11) SCC2 (42) SCC3 (173)
Point source
Combustion in energy industries
- Public power - District heating plants - Petroleum refining plants - Commercial power
4
Combustion in manufacturing industries
- Process furnace - Combustion plants - Other
44
Production processes
- Processes in other industries - Processes in wood, paper and pulp industries - Processes in inorganic chemical industries - Processes in petroleum industries - Processes in food and drink industries - Ammonia consumption - Processes in organic chemical industries - Processes in iron and steel industries
44
Waste treatment and disposal - Waste incineration - Other waste treatment 5
Area source
Non-industrial combustion - Commercial and institutional plants - Plants in agriculture, forestry and aquaculture - Residential plants
5
Storage and distribution of fuels - Gasoline distribution 3
Solvent utilization
- Paint application -Electronic Degreaser - Dry cleaning - Other use of solvents and related activities
15
Agriculture - Enteric fermentation - Cultures with fertilizers 10
Other area sources - Forest and other vegetation fires - Animals 3
Mobile source
Road transport
- Passenger cars - Light-duty vehicles - Recreational vehicles - Taxis - Buses - Special purpose vehicles - Trucks - Motorcycles
18
Non-road transport
- Construction machinery and equipment - Agricultural machinery - Ships - Railways - Aircrafts
22
*The numbers represent the number of sources. 83
84
6
85
Fig. S3. Frequency distribution of TGM during sampling period. Note that TGM was measured every 5-min.
7
86 Fig. S4. The diurnal variations of co-pollutants concentrations and 87 meteorological data during the sampling periods. The error bars represent 88 standard error. 89
90
8
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
Total (d
aytim
e)
Total (n
ighttime)
TGM
conc
. (ng
m-3
)
0
10
20
30
40
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
Total (d
aytim
e)
Total (n
ighttime)
NO
2 con
c. (p
pb)
0
20
40
60
80
100
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
O3 c
onc.
(ppb
)
0
20
40
60
80
100
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
Total (d
aytim
e)
Total (n
ighttime)
CO co
nc. (
ppb)
0
1000
2000
3000
4000
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
Total (d
aytim
e)
Total (n
ighttime)
PM10
conc
. (g
m-3
)
0
50
100
150
200
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
Total (d
aytim
e)
Total (n
ighttime)
SO2 c
onc.
(ppb
)
0
10
20
30
40
50
Spring (da
ytime)
Spring (n
ighttime)
Summer (da
ytime)
Summer (nighttim
e)
Fall (da
ytime)
Fall (n
ighttime)
Winter (da
ytime)
Winter (n
ighttime)
Total (d
aytim
e)
Total (n
ighttime)
Tem
pera
ture
(
℃ )
-10
0
10
20
30
40
91
Fig. S5. Comparison of TGM, co-pollutants and meteorological data between daytime 92 and nighttime. Note that TGM was presented with hourly average concentration. 93 94
9
95
Fig. S6. Comparisons of CPF and CBPF plots for TGM and CO higher than average 96 concentration. The radial axes of CPF and CBPF are the probability and the wind 97 speed (m s-1), respectively. 98
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